Affiliations: [a] Bozhou Vocational and Technical College, Information Technology Department, Bozhou, Anhui, China | [b] School of Pharmacy of Bozhou Vocational and Technical College, Bozhou, Anhui, China
Correspondence:
[*]
Corresponding author: Qun Chen, School of pharmacy of Bozhou Vocational and Technical College, Bozhou, Anhui 236813, China. E-mails: [email protected] and [email protected].
Abstract: In order to capture autobiographical memory, inspired by the development of human intelligence, a computational AM model for autobiographical memory is proposed in this paper, which is a three-layer network structure, in which the bottom layer encodes the event-specific knowledge comprising 5W1H, and provides retrieval clues to the middle layer, encodes the related events, and the top layer encodes the event set. According to the bottom-up memory search process, the corresponding events and event sets can be identified in the middle layer and the top layer respectively; At the same time, AM model can simulate human memory roaming through the process of rule-based memory retrieval. The computational AM model proposed in this paper not only has robust and flexible memory retrieval, but also has better response performance to noisy memory retrieval cues than the commonly used memory retrieval model based on keyword query method, and can also imitate the roaming phenomenon in memory.
Keywords: Artificial intelligence, cognitive model, autobiographical memory, roaming in memory
